Journal of the American Chemical Society最新文献

Dothideomins are antibacterial bis(anthraquinone) polyketides isolated from the endophytic fungus Dothideomycetes sp. BMC-101, featuring a unique 6/6/6/5/6/6/6 heptacyclic scaffold imbedded with a tricyclo[5.2.2.0.^4,8]undecane core. Although the structures and antibacterial potential are attractive, the biosynthesis process and the formation of a heptacyclic scaffold, especially the tricyclo[5.2.2.0.^4,8]undecane cage-like core, are unclear. Here, we elucidated the biosynthesis of dothideomins C and D encoded by a dot gene cluster through heterologous expression, in vivo feeding experiments, and in vitro biochemical assays. Our findings reveal an enzyme cascade involved in the conversion of the precursor emodin into dothideomins. Specifically, the cytochrome P450 monooxygenase DotG is shown to solely catalyze the unprecedented formation of triple C-C bonds and construct the tricyclo[5.2.2.0.^4,8]undecane-embedded skeleton. This study enhances the comprehension of the P450 enzyme-controlled formation of complex natural products.

Immunotherapy has attracted widespread attention because of its durable and effective antitumor properties. However, systemic delivery strategies often result in immune-related off-target toxicity effects and inadequate drug retention at the tumor site, which limits its broader application. In this research, we designed a dual-functional antitumor peptide (N-Pep) that serves as both a therapeutic agent and metal ions (Mn²⁺) immunomodulator carrier. The rational designed antitumor peptide self-assembles into a hydrogel through coordination with Mn²⁺ ions (referred to as N-Pep-Mn gel). The multiporous hydrogel network allows for efficient loading of antiprogrammed death-1 antibody (αPD-1). The hydrogel served as a depot for the sustained release of Mn²⁺ ions and encapsulated αPD-1, effectively activating dendritic cells, polarizing tumor-associated macrophages and enhancing effector T cell infiltration, thereby leading to the effective inhibition of tumor growth through intratumoral and systemic immune responses. Additionally, the hydrogel induces robust immune memory, providing substantial protection against tumor recurrence. These findings underscore the potential of Mn²⁺ ion-coordinated antitumor peptide hydrogel as an advanced platform for enhancing antitumor immunotherapy.

Identifying unknown molecules beyond existing databases remains challenging in surface-enhanced Raman scattering (SERS) spectroscopy. Conventional SERS analysis relies on matching experimental and cataloged spectra, limiting identification to known molecules in databases. With a vast chemical space of >10⁶⁰ molecules, it is impractical to obtain the spectra of every molecule and rely solely on in silico techniques for spectral predictions. Here, we showcase an ML-based SERS chemical space that leverages key spectra-structure correlations to achieve two-way spectra-to-structure and structure-to-spectra predictions for untrained molecules with a >90% average accuracy. Using a SERS chemical space comprising 38 linear molecules from four classes (alcohols, aldehydes, amines, and carboxylic acids), our experimental and in silico studies reveal underlying spectral features that enable the prediction of untrained molecules represented by two molecular descriptors (functional group and carbon chain length). For forward spectra-to-structure predictions, we devise a two-step "classification and regression" ML framework to sequentially predict the functional group and carbon chain length of untrained molecules with 100% accuracy and ≤1 carbon difference, respectively. In addition, using an eXtreme Gradient Boosting (XGBoost) regressor trained on the two molecular descriptors, we attain inverse structure-to-spectra prediction with a high average cosine similarity of 90.4% between the predicted and experimental spectra. Our ML-based SERS chemical space represents a shift in molecular identification from traditional spectral matching to predictive modeling of spectra-structure relationships. These insights could motivate the expansion of SERS chemical spaces and realize demands for present and future SERS technologiesfor accurate unknown identification across diverse fields.

Ammonia (NH₃) is a promising carbon-free fuel when prepared from sustainable resources. First-row transition metal electrocatalysts for ammonia oxidation are an enabling technology for sustainable energy production. We describe electrocatalytic ammonia oxidation using robust molecular complexes based on Earth-abundant iron. Electrochemical studies of ferrocenes with covalently attached pyridine arms reveal facile ammonia oxidation in DMSO (2.4 M NH₃) with modest overpotentials (η = 770-820 mV) and turnover frequencies (125-560 h^-1). Experimental and computational studies indicate that the pendant pyridyl base serves as an H-bond acceptor with an N-H bond of ammonia that transfers a proton to the pyridine following oxidation by the attached ferrocenium moiety in a proton-coupled electron transfer (PCET) step. This generates an amidyl (^•NH₂) radical stabilized via H-bonding to a pendant pyridinium moiety that rapidly dimerizes to hydrazine (H₂N-NH₂), which is easily oxidized to nitrogen (N₂) at the glassy carbon working electrode. This report identifies a general strategy to oxidize ammonia via H-bonding to a base (B:), thereby activating [B···H-NH₂] toward PCET by a proximal oxidant to form [BH···NH₂]^+/• radical cations, which are susceptible to dimerization to form easily oxidized hydrazine.

Heteroatom-doping has emerged as a transformative approach to producing high-performance catalysts, yet the current trial-and-error approach to optimize these materials remains ineffective. To enable the rational design of more efficient catalysts, models grounded in a deeper understanding of catalytic mechanisms are essential. Existing models, such as d-band center theory, fall short in explaining the role of dopants, particularly when these dopants do not directly interact with reactants. In this study, we synthesize various heteroatom-doped catalysts to explore the correlation between the electronic effects of the dopants and catalyst activity. Using Co-MoS₂ as a model catalyst and the Li-S redox reaction within the cathode of Li-S batteries as a test system, we show the interaction between cobalt sites and adjacent lattice sulfur atoms disrupts the intrinsic structural and electronic symmetry of MoS₂. This disruption enhances the transfer of spin-polarized electrons from metal centers to lattice sulfur and promotes the adsorption of reactant intermediates. Furthermore, by analyzing 20 different dopant elements, we establish a linear relationship between the electron density in the lattice sulfur and catalyst activity toward the reduction of sulfur species, a relationship that extends to other catalytic systems, such as the hydrogen evolution reaction.

Ancient Egyptian mummification was a mortuary practice aimed at preserving the body and soul for the afterlife, achieved through a detailed ritual of embalming using oils, waxes, and balms. While most research on Egyptian mummified bodies has so far been conducted in European collections, our study focuses on the collection of the Egyptian Museum in Cairo. The goal was to evaluate whether contemporary smells reflect the mummification materials and, if so, what information can be of value to collection interpretation and conservation. We combined panel-based sensory analyses with gas chromatography-mass spectrometry-olfactometry (GC-MS-O), microbiological analysis, and historical and conservation research. Apart from differences in odor intensity, the sensory analyses highlighted common olfactory descriptors for all samples: "woody", "spicy", and "sweet". GC-MS-O identified four categories of volatiles based on their origin: (i) original mummification materials; (ii) plant oils used for conservation; (iii) synthetic pesticides; and (iv) microbiological deterioration products. However, the use of insect repellents similar in composition to the original mummification materials makes it challenging to attribute the origin of some compounds. Clusters based on the chemical and olfactory profiles of the smells emerged, suggesting similarities based on the archeological period, conservation treatments, and materiality.

Pulmonary macrophages undergo dynamic changes in population, proportion, and polarization during respiratory diseases. Monitoring these changes is critical for understanding their roles in pathology, improving the diagnosis, and guiding drug development. However, current analytic methods based on tissue biopsy are invasive and static, limiting their ability to provide such dynamic information. Herein, we report a dual-locked macrophage-specific renal-clearable probe (DMRP_NOCas) for the dynamic monitoring of pulmonary macrophages during influenza A virus (IAV) infection. DMRP_NOCas activates fluorescence in the presence of two biomarkers (caspase-1 and NO) only coexpressed by M1 macrophages. To optimize the NO reactivity, the scaffold of DMRP_NOCas is screened from the hemicyanine derivatives with an o-phenylenediamine group positioned differently on the indole ring. Notably, the para-substituted o-phenylenediamine demonstrates a higher NO-activated fluorescence compared to its meta-substituted counterpart. This enhancement, as revealed by quantum chemical calculations, is attributed to differential inhibition of twisted intramolecular charge transfer induced by the NO reaction. DMRP_NOCas specifically distinguishes M1 macrophages from other leukocytes including T cells, neutrophils, and M2 macrophages, a capability unmatched by single-locked control probes and other reported probes. Consequently, DMRP_NOCas enables in vivo dynamic monitoring of pulmonary macrophages, uncovering extensive recruitment and M1 polarization of monocyte-derived macrophages within 48 h of IAV infection. This process is accompanied by a significant reduction in alveolar macrophages. These findings provide new insights into macrophage-mediated pulmonary inflammation and underscore the potential of dual-locked probes for precise diagnosis and monitoring of pathological processes.

Isothermal techniques for amplifying nucleic acids have found extensive applications in genotyping and diagnostic tests. These methods can be integrated with sequence-specific detection strategies, such as CRISPR-based detection, for optimal diagnostic accuracy. In particular, recombinase-based amplification uses proteins from the Escherichia virus T4 recombination system and operates effectively at moderate temperatures in field and point-of-care settings. Here, we discover that recombinase polymerase amplification (RPA) is controlled by liquid-liquid phase separation, where the condensate formation enhances the nucleic acid amplification process. While two protein components of RPA could act as scaffold proteins for condensate formation, we identify T4 UvsX recombinase as the key regulator orchestrating distinct core-shell arrangements of proteins within multiphase condensates, with the intrinsically disordered C-terminus of UvsX being crucial for phase separation. We develop volumetric imaging assays to visualize RPA condensates and the reaction progression in whole volumes, and begin to dissect how macroscopic properties such as size distribution and droplet count could contribute to the overall reaction efficiency. Spatial organization of proteins in condensates may create optimal conditions for amplification, and disruption of such structures may diminish the amplification efficiency, as we demonstrate for the case of reverse transcription-RPA. The insight that RPA functions as a multiphase condensate leads us to identify the UvsX^D274A mutant, which has a distinct phase-separation propensity compared to the wild-type enzyme and can enhance RNA detection via RPA-coupled CRISPR-based diagnostics.